Python Basics: A Beginners Course and Solved Exercises

Python Basics: A Beginners Course and Solved Exercises, available at $54.99, has an average rating of 4.75, with 64 lectures, 2 quizzes, based on 38 reviews, and has 211 subscribers.

You will learn about Master python basics, variables types, conditional statements, loops and functions Practice using exercises with solutions to kick start your Python skills Identify needed functionalities to provide basic solutions in Python Acquire a better understanding of the potential of Python programming Write simple solutions in Python This course is ideal for individuals who are Beginner Python enthusiasts and aspiring data scientists It is particularly useful for Beginner Python enthusiasts and aspiring data scientists.

Enroll now: Python Basics: A Beginners Course and Solved Exercises

Summary

Title: Python Basics: A Beginners Course and Solved Exercises

Price: $54.99

Average Rating: 4.75

Number of Lectures: 64

Number of Quizzes: 2

Number of Published Lectures: 64

Number of Published Quizzes: 2

Number of Curriculum Items: 66

Number of Published Curriculum Objects: 66

Original Price: $44.99

Quality Status: approved

Status: Live

What You Will Learn

Master python basics, variables types, conditional statements, loops and functions
Practice using exercises with solutions to kick start your Python skills
Identify needed functionalities to provide basic solutions in Python
Acquire a better understanding of the potential of Python programming
Write simple solutions in Python

Who Should Attend

Beginner Python enthusiasts and aspiring data scientists

Target Audiences

Beginner Python enthusiasts and aspiring data scientists

Welcome to the Python course! Python is a high-level, interpreted, and general-purpose dynamic programming language that is widely used for data analysis, web development, artificial intelligence, and much more. With its simplicity, versatility, and vast library of modules, Python is an ideal language for beginners and experienced programmers alike.

How to follow this course: In this course, you will be guided through the basics of the Python language and its various features, with a focus on hands-on examples and practical applications. The course is designed for students with no prior experience in programming, but those with some prior experience will also benefit from the in-depth coverage of the language. To maximize your learning experience, it is recommended that you actively participate in the course by following along with the examples, completing the exercises, and asking questions when you need help.

Course content description: The course will cover the following topics:

Introduction to Python and its features
Installing Python and setting up the environment
Variables and basic data types, including integers, floating-point numbers, strings, and booleans
Containers, including lists, tuples, and dictionaries
Basic operators, including arithmetic, assignment, comparison, and logical operators
Conditional statements, including if, else, and elif
Loops, including for and while loops
Comprehensions, a powerful feature for generating and processing lists and dictionaries
Functions and modules, including how to define and call functions, import modules, and create custom modules
Working with files, including how to read and write data to and from files.

Learning values for students:

Introduction to Python and its features: In this section, students will be introduced to the basics of Python, including its history, features, and applications. They will also learn how to install and run Python on their own computer.
Variables and basic data types: In this section, students will learn how to declare variables, store values in them, and manipulate the data stored in variables. They will also learn about the various data types available in Python, including integers, floating-point numbers, strings, and booleans.
Containers: In this section, students will learn about containers, including lists, tuples, and dictionaries, and how they can be used to store and manipulate data. They will also learn how to access, modify, and manipulate elements in containers.
Basic operators: In this section, students will learn about basic operators in Python, including arithmetic, assignment, comparison, and logical operators. They will also learn how to use these operators in expressions to perform operations on data.
Conditional statements: In this section, students will learn about conditional statements, including if, else, and elif, and how they can be used to control the flow of a program based on certain conditions.
Loops: In this section, students will learn about loops, including for and while loops, and how they can be used to repeat operations or process data.
Comprehensions: In this section, students will learn about comprehensions, a powerful feature in Python for generating and processing lists and dictionaries.
Functions and modules: In this section, students will learn about functions and modules, including how to define and call functions, import modules, and create custom modules. They will also learn how to organize their code into reusable and modular components.
Working with files: In this section, students will learn how to read and write data to and from files, a crucial skill for working with large amounts of data. They will learn about different file formats, such as text files and CSV files, and how to open, read, write, and close files in Python.

In conclusion, this course offers a comprehensive introduction to the Python language and its various features, with a focus on hands-on examples and practical applications. By the end of the course, students will have gained a solid foundation in Python and be able to use it to perform a wide range of data analysis, web development, and artificial intelligence tasks. The course is designed to be both challenging and rewarding, providing students with the skills and knowledge they need to continue learning and growing as a programmer.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Course Introduction

Lecture 2: About This Course

Lecture 3: How To Follow This Course

Lecture 4: Course Content Summary

Chapter 2: Installing Python

Lecture 1: Installation Options

Lecture 2: Installing Anaconda

Lecture 3: First Python Code In Jupyter

Lecture 4: Saving And Opening Your Files

Lecture 5: Chapter Content Recap

Chapter 3: Variables And Basic Data Types

Lecture 1: Variables And Basic Data Types 1/3

Lecture 2: Variables And Basic Data Types 2/3

Lecture 3: Variables And Basic Data Types 3/3

Lecture 4: Casting Variables 1/2

Lecture 5: Casting Variables 2/2

Lecture 6: Print() Function 1/2

Lecture 7: Print() Function 2/2

Lecture 8: Input() Function

Lecture 9: Section Content Summary

Chapter 4: Containers In Python

Lecture 1: Lists 1/2

Lecture 2: Lists 2/2

Lecture 3: Tuples 1/2

Lecture 4: Tuples 2/2

Lecture 5: Sets 1/2

Lecture 6: Sets 2/2

Lecture 7: Slicing 1/3

Lecture 8: Slicing 2/3

Lecture 9: Slicing 3/3

Lecture 10: Dictionaries 1/2

Lecture 11: Dictionaries 2/2

Lecture 12: Section Content Summary

Chapter 5: Basic Operators

Lecture 1: Introducing Operators

Lecture 2: Arithmetic Operators

Lecture 3: Assignment Operators

Lecture 4: Comparison Operators

Lecture 5: Logical Operators

Lecture 6: Membership Operators

Lecture 7: Identity Operators

Lecture 8: Operators Precedence

Lecture 9: Section Content Recap

Chapter 6: Conditional Statement

Lecture 1: Conditional Statement

Lecture 2: Nested Conditional Statement

Lecture 3: Ternary Conditional Statement

Lecture 4: Conditional Statement Recap

Chapter 7: Loops And Iterations

Lecture 1: For Loops

Lecture 2: While Loops

Lecture 3: Break And Continue Statement

Lecture 4: Nested Loops

Lecture 5: Section Content Recap

Chapter 8: Comprehensions

Lecture 1: Comprehensions In Python

Lecture 2: Types Of Comprehensions

Lecture 3: Nested Comprehensions

Lecture 4: Comprehensions Section Recap

Chapter 9: Functions

Lecture 1: Defining Functions

Lecture 2: Variables Scope

Lecture 3: Recursive Functions

Lecture 4: Modules

Lecture 5: Lambda Functions

Lecture 6: Section Summary

Chapter 10: Working With Files

Lecture 1: Opening And Reading Files

Lecture 2: Writing In Files

Lecture 3: CSV Files

Lecture 4: JSON Files

Lecture 5: Section Summary

Chapter 11: Practice Exercises

Lecture 1: Practice Exercises And Solutions

Instructors

Dr Ziad Francis
PhD, Data Scientist

Rating Distribution

1 stars: 0 votes
2 stars: 0 votes
3 stars: 2 votes
4 stars: 13 votes
5 stars: 23 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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